The problem of red-eye is well-known in photography. Red-eye is caused by light from a camera's flash being reflected off blood vessels in a subject's retina back to the camera. Occurrence of red-eye may increase when the subject's pupils are wide open, as in a darkened room.
Various red-eye reduction algorithms have been developed to identify instances of red-eye in an image and correct them. Some algorithms perform face detection, then locate the eyes within a detected face, and finally correct for the redness of the eye. Face detection algorithms, however, are generally computation-intensive and put great demands on a computing system's power source. This makes face detection algorithms undesirable for use in some portable devices such as camera phones, which have limited computational capabilities compared to desktop computers, and must make judicious use of battery power.
Disclosed herein are computationally efficient red-eye correction techniques well-suited for devices such as camera phones.